William Wallace - US grants

This proposal is for funding to cover partial cost of conducting the conference "Global Manufacturing: Technological and Economic Opportunities, and Research Issues" to be held at PRI in October 1987. The purpose of this conference is to foster an awareness of the technical, managerial and policy issues, both national and international, that are involved in global manufacturing and to delineate a research agenda that will contribute to our understanding of the complexities inherent in global manufacturing. To achieve this goal, scholars actively engaged in research on the selected topics will be invited to be speakers. The topics to be addressed will focus on the technical, economic and public policy issues relating to the future of automated manufacturing, advances in communications and computer technologies, management of human resources, and national and international competition and cooperation. The speakers will be from key industrial nations. Discussion of each topic will be led by a panel composed of 3 to 5 individuals including a U.S. industrialist, a foreign manufacturer, an academic, and a discussant/rapporteur who will prepare a written synopsis of the panel proceedings, focusing on needs for research. The proceedings of this conference will be published.

The project undertakes the visit to the site of the Exxon Valdez oil spill in Alaska on March 24, 1989, for the gathering of perishable data on the immediate and long- term impacts of the oil spill, as well as on the actual emergency response, management and mitigation actions. Cataloguing the ongoing and ensuing documentation will be used to identify gaps in reports and in forthcoming analyses. A multidisciplinary team of researchers will provide the necessary systematic approach to determine the effectiveness of the decision making and support systems used to cope with the disaster.

This grant will support an interactive distance video workshop on Ethics in Modeling. The purpose of the workshop is to explore the use of this new technology as a means to focus attention on ethical issues in the development and use of computer-based decision models for the modeling community that develops models; the potential users and those who may be affected by the use of models; and educators and researchers in applied ethics and the disciplines of modeling: operations research, statistics, management science, and systems engineering. The workshop will involve individuals at four sites, in the Netherlands, Massachusetts, Maryland, and New York. One goal of the workshop is to find out what modes of interaction using this technology will be most effective. The second research goal is to generate awareness, discussion, and scholarship on the ethical issues involved in modeling. For this purpose, the participants will discuss four cases. Each site will have a facilitator, and the workshop will be videotaped for analysis. Participants will complete pre- and post- workshop questionnaires. The principal investigators will prepare a report on the findings.

Wallace Visualization is becoming an increasingly important part of modeling as a result of the integration of computer graphics into modeling software. In addition, technological advances are making it possible for rapidly growing numbers of the general population to become modelers, for example, by using spreadsheet software. The proposed research is based upon our previous experimental work, our theory of the role of visualization in modeling, and the literature on visualization and cognitive science. We have selected as the target of our visualization a component that is central to the modeling process and to our understanding of it: the heuristics sued in constructing models. In order to assess our theory, we intend to build visualization systems for two different types of modeling tasks, one in a physical domain, and the other in an abstract domain. The first experiment will be conducted in the physical domain of groundwater modeling with the Where Next heuristics visualization system. The second experiment will be conducted in the physical abstract domain of machine learning as applied to consumer credit. As part of our experimentation, we will construct a `modeler's assistant` for each of the problem domains. The contributions of the research are to better understand the process of modeling and the role of visualization in this process, and to integrate visualization techniques into the process of modeling in order to capitalize upon advances in computer graphics technology. ?¢ ?Á¢?À>Á? ¥? ?Á _?%¥? ??¢???%?>/?` ?>>/¥??Á &/?¥????/>¥¢ ??%% ??_Á Â??_ / ???Á ?/>ÀÁ ? /?/?Á_?? /?Á/¢ ?>?%???>À Á??>?_??¢ ??%?¥??/% ¢??Á>?Á />¥©????%?À` /?_?>?¢¥?/¥??Á ¢??Á>?Á />? %/? ¿> /???¥??> ??/?¥?¥??>Á?¢ Â??_ ??¥© ¥©Á ó/>/??/> />? ¡ ½ À??Á?>_Á>¥¢ ??%% ?Á ?>??%?Á? /¢ ??Á¢Á>¥Á?¢ ??__Á>¥/¥??¢ />? ??¢??¢¢/>¥¢

The objective of this research is to provide the knowledge base to improve the capability of emergency response organizations to improvise. The need for support in improvisation in the form of training and real-time decision aids is well recognized. The theoretical bases for this project will be a decision logic which models cognitive processes in improvisation as evinced, for example, in documented cases of emergency response. In the first of three experiments, the efficancy of the decision logic will be assessed with respect to its ability to support decision makers in fashioning improvisations which are relevant to a task in real-time provlem solving. For the final experiments, the logic will be embedded in a decision support system and tested in two separate gaming situations, one in Eurpoe and one in the United States. The principal contributions of this research will be in providing (1) guidelines as embodied in training materials and a decision aid for preparing emergency managers in improvise, and (2) a decision support system for the processof improvisation in emergency response.

The topic of trust and its influence on consumer behavior has received growing attention of late with respect to electronic commerce, especially with regard to establishing and evaluating the trustworthiness of a single web site. However, consumers who rely on the Internet for information gathering are better served by tools that integrate information from many different sources and measure the trustworthiness of the integrated body of information. We propose to develop a methodology that addresses this problem of assembling an information product from many sources and evaluating its trustworthiness. Drawing on techniques in text analysis, knowledge acquisition, graph theory and visualization, and statistical inference, we will enable the user to generate an automated summary from a group of web pages, evaluate its trustworthiness, and visually navigate the information models. The final deliverable is a software package that implements the methodology. The proposed research will benefit the Internet community by providing a new technology that fills the void left by current information retrieval and trust assessment technologies. In addition, the techniques we propose to develop have the potential to contribute to a wide variety of fields confronted with the problem of analyzing samples of graph-valued data.

Impact of the World Trace Center Disaster on Critical Infrastructure Interdependence
This exploratory research focuses on time sensitive data and field research related to the devastating impacts of the terrorist attacks on the World Trade Center (WTC) in New York City, NY on September 11, 2001. The objective of this research is to increase our knowledge base of and model the interdependencies of critical infrastructure systems with the aim of understanding their vulnerabilities to disasters of this type and scale. A systems approach will be used to represent 1) designed or intended infrastructure interdependencies; 2) the impacts of the attack overall and during emergency response; and the effects and needs related to interdependencies during recovery operations. Much of the information will only be available in the early phases of response.
Infrastructure interdependencies have been identified by Presidential Decision Directive 63 as a part of the Critical Infrastructure Protection initiative. Understanding interdependencies is key to efficient funds allocation for design, construction, operations, maintenance, operations and security of our nation's infrastructure. Interdependencies imply the potential for cost-efficiencies through redundancy reductions as well as disastrous vulnerabilities through cascading losses of lifelines and lives. This results of this research will be used to identify opportunities for reducing vulnerabilities, developing countermeasures to mitigate the impacts of disruptions, and guide actions for response and recovery.

The nature of the terrorist attacks on the World Trade Center in New York City demonstrates the need for understanding the interdependencies between physical infrastructure and social networks. The benefits of such understanding may include possible recommendations on modifying the design of the physical infrastructures to improve their resilience to catastrophic disruptions. Models of social networks relying on wireless and wired communication infrastructures would allow the development and testing of efficient algorithms to determine critical blocks in the infrastructures, whose distraction will adversely affect the communication traffic inside of and among social networks. This research project will use the graph-theoretic approach to model social networks and their reliance on physical infrastructures, focusing mainly on social networks in the New York City area and the providing infrastructures, including telephone networks, towers for the wireless communication, transportation and emergency services. This knowledge will be used to identify opportunities for reducing vulnerabilities, developing countermeasures to mitigate the impact of disruptions, and guiding actions for timely response and discovery.

The objective of the research is to help ensure an efficient, effective
and equitable distribution of resources in responding to events that
cause disruption in infrastructure systems and to aid in designing
infrastructure systems that are robust under disruptions, due to
natural, human-caused or willful acts. The approach is to develop a
clear and unambiguous set of definitions of critical infrastructure
interdependencies; a mathematical representation of infrastructure
systems that incorporates interdependencies among and between systems;
algorithms that can be used to run the model(s) for vulnerability
assessment and emergency response; and a human-computer interface for
user interaction with the model.

If successful, the benefits will be an improved ability to both mitigate
the impact of and respond to events that have the capability to cause
large-scale, potentially catastrophic damage to critical infrastructure
systems. Critical infrastructure systems provide services that are
essential to both the economy and well-being of nations and their
citizens. As documented in a recent report to the U.S. Congress, it is
of vital importance that these services not be degraded, whether by
willful acts such as terrorism or by natural or random events such as
earthquakes. The research will permit different act and event scenarios
to be modeled, and their impact on the service provided by an
infrastructure system assessed. The result would be infrastructure
systems that are designed to be more resilient to disruptions, with the
expected loss of service reduced and the required level of service
restored more quickly.

Critical infrastructure systems provide services that are essential to both the economy and well-being of nations and their citizens. As documented in a recent report to the U.S. Congress, it is of vital importance that these services not be degraded, whether by willful acts such as terrorism or by natural or random events such as earthquakes, design flaws or human error. Yet infrastructure systems and the organizations that manage them are now recognized as components of highly-coupled systems that increasingly rely on one another in order to deliver key services.

The objective of the research is to improve understanding of and support for the management of interdependent critical infrastructure systems. Infrastructure interdependence occurs when, due to either geographical proximity or shared operations, an impact on one infrastructure system is also an impact on one or more other infrastructure systems. The particular focus of the research is on developing techniques that can be used either to mitigate against or respond to events that have the capability if impacting interdependent critical infrastructure systems and to provide decision makers with means of manipulating these models for purposes of mitigation or response. The models developed in the research will be embedded in computer-based decision aids. Such computer-based decision support is intended to assist decision makers in reducing expected loss of service due to disruption and in restoring service more quickly if loss of service actually occurs.

The broader impacts of the research will improve society's ability to withstand the impact of and respond to events that can disrupt the provision of services that are required for the health, safety and economic well being of the citizenry. Managers of critical infrastructures and emergency response officials will be able to model different event scenarios and assess their impact on the services provided by critical infrastructure systems. With this knowledge, mitigation and preparedness strategies can be formulated and evaluated for their ability to prevent an emergency from escalating into a disaster and, if a disaster does occur, ensure a rapid restoration of critical services.

It is proposed to develop models and algorithms for identifying groups that camouflage their functioning in a large communication network. Since the communications of an aberrant group are often encrypted or unreliable, it is proposed to develop algorithms that use only communication intensities, and do not rely communication semantics. The results of this research can also be used for the early detection and monitoring of aberrant groups that may be planning/coordinating undesirable activities. Tools will be developed that provide a first defense against such activities and therefore have wider impact in national security and defense. The proposed work is distinguished from prior research in two ways. The first is that the brand-new problem of detecting the hidden group itself, using only communication data, will be studied. The most relevant work lies in the social network literature wherein it is assumed that the members of the aberrant group are already known and one studies, for example, how certain actions affect properties of the network such as its stability or communication potential. The second is that in order to accomplish the task, novel methodologies will be developed:

i. The communications will be modeled as a Hidden Markov Model (HMM). The state space corresponds to the group structure of the society, where a group is a collection of individuals with some commonality. The hidden (aberrant) group constitutes one of the groups that participates in the communications. The model of how the social groups evolve and communicate can be learned: given the prior communication behavior of the society, a HMM is calibrated to the prior behavior. If this HMM does not adequately explain the present behavior, but a HMM which incorporates a hidden group does, then one can determine the existence of the hidden group as well as its members.
ii. Combinatorial algorithms will be used to detect persistent hidden group communication structures as candidate initial hidden groups. Such structures include simple cycles, trees, cliques, stars and wheels. The results of such algorithms will be used as initial candidate hidden groups that can be fine-tuned using the HMM approach. The algorithms will be designed and tested on simulated test beds, as well as on real communication data such as newsgroups. While the primary goal is to develop tools for detecting hidden groups, the tools will also provide a vehicle for integrating education with the research. Models of evolving societies and hidden groups will be developed that will allow K-8 through high-schools to "test" their understanding of societal behavior by attempting to predict whether there is a hidden group, who the members are, and comparing their predictions with the automated "computer" predictions and the true answer. Such a model will be implemented at RPI on a web server and at the Junior Museum in Troy, NY. The goal of such demonstrations is to improve students' understanding of the behavior of communication networks and detection of anomalous behavior. In addition, this research will be incorporated into a research-oriented, interdisciplinary educational experience for students who otherwise might never be involved in such research. By conducting cross-disciplinary research involving mathematical, computer and social sciences, the pool of eligible research assistants will be broadened, which will significantly increase the possibility of identifying qualified candidates from underrepresented groups.

This award is supported jointly by the NSF and the Intelligence Community. The Approaches to Combat Terrorism Program in the Directorate for Mathematical and Physical Sciences supports new concepts in basic research and workforce development with the potential to contribute to national security.

This project will develop novel methods for the statistical analysis of the evolution of social groups acting within a large social network via a communications network, such as the Internet. The basis for the analysis is a set of probabilitistic laws (micro-laws) that govern the individual behavior of actors, which largely determines the macro-evolution of the social groups. The parameters of the macro-evolution can be measured and then used to determine, via reverse engineering, the parameters of the micro-laws that fit the observed evolution. Understanding the evolution of social communities will help determine resource allocation strategies for enhancing the functioning of these communities. The methods developed in this research can be used to locate, within a large social network, social groups that try to hide their inner communications. Such a system can be instrumental in preventing terrorists' attacks similar to those on September 11, 2001. The proposed research will also open up novel educational opportunities at the home university related to social network analysis.

The proposed research seeks to explore how values are embedded in computational models, how these values are shaped by professional and organizational culture, and the effects of these embedded values on the success of computational models as products. In order to accomplish these objectives, three hypotheses will guide the research: 1) that the values embedded in computational models will partially, but not fully, correspond to those found in sociology and science and technology studies literatures, but additional values specific to computational models will also be identified; 2) that the ethical frameworks of the organization and the profession partially, but not fully, determine what values are embedded during the modeling process; and 3) that the embedding of values in computational models is a significant aspect of their development, and thus that the success or failure of a model as a product is partially, but not fully, determined by what values are embedded during the modeling process. This project emerges at the intersection of the process of modeling and the ethics of modeling. These two threads are inseparably interlinked, since professional and organizational ethics play a role in shaping the process of modeling, while an understanding of the process of modeling is necessary in order to understand how values become embedded in computational models. To test these hypotheses and achieve these objectives, it is necessary to employ a multiple-methodology approach to data collection and analysis. At the selected field site, a computational modeling laboratory, the researchers will utilize structured questionnaires, interviews, participant observation, and focus groups to study the process of computational modeling. Data analysis will be both quantitative and qualitative, and will be based on statistical methodologies, behavioral analysis, and content analysis. The purposes of this exploratory study are to demonstrate the validity of the proposed methodology by conducting all four data collection approaches with corresponding data analyses for one field site, while at the same time producing valuable data about the ethical implications of values embedded in computational models. This project builds on the experience and strengths of both researchers, including prior NSF-sponsored research. One of the PIs has forty years of experience as a computational modeler, including research on the ethics of modeling, while the other PI has an educational background in computer science, anthropology, and science and technology studies. This study, first, aims to contribute to the literature on the ethics of modeling by providing an in-depth case study of the ethics and values of computational modeling. Second, the methodology for conducting in-depth field data collection and analysis will contribute to the literature on professional and organizational culture and ethics. Finally, the study will also contribute by bringing together the literatures on models as products and modeling as a process, which can lead to a better understanding of the effect that embedding specific values during the process of computational modeling can have on the success of the computational model as a product. The first social contribution of this study will be to improve the practice of computational modeling by demonstrating to modelers how values are embedded in the models that they produce and the ethical implications of these embedded values. A second social contribution of this study will be to make modelers more aware of the constraints of their organizational cultures. Finally, the findings of this and subsequent research can eventually lead to the development of online modules for educating computer science students in the ethics of modeling, which would provide computer science programs with a free resource that they could use to develop ethics courses.

This SGER project is in response to the Sumatra-Andaman Island earthquake and Indian Ocean tsunami disaster. The project will study the functioning of communication networks and their use by various social groups to better understand how sensor technologies could be best deployed and integrated into global communication networks. Such research is necessary to avoid what happened during this disaster where despite the fact that the tsunami hit land two hours before hitting India and Sri Lanka, no warning signal propagated to these regions. The proposed research will build models of how information flows in a communication network, taking into account the "trustability" of the information. The broader impacts of this research will speak to what went wrong and the provision of recommendations to avoid such a situation in the future. Under high stress conditions, where parts of a communication network may be destroyed or disrupted, the nature of social communication networks will change. The objective is to understand how they changed and how information flow relating to the disaster was affected. Ultimately, the goal is to provide concrete suggestions for how to improve social communication networks so as to allow warning messages to flow under situations of disruption and destruction.

This project, funded as a NSF SGER in response to Hurricane Katrina, is a scholarly study of organizational constraints on federal disaster activities of the Federal Emergency Management Agency (FEMA) and the U.S. Coast Guard. The research will consist of data collection about perceptions of each organization's performance in Hurricane Katrina, analysis of rule-making and budgetary changes in affecting each organization's outputs, and initial development of a dynamic model of organizational processes. The organizational process model will focus on the dynamics of agency adoption of new missions where agency information processing capacity is serial rather than parallel.

The project team will collect secondary data from publicly available data archives and a limited number of interviews in order to better understand the changes over time in organizational structures and responsibilities for federal emergency management. These interviews are to be selected as a dozen or so individuals among current and prior congressional and agency staff who can provide insights about these issues. The data will be used to develop the model and to report on the particular organizational bottlenecks in emergency management.

This research is a collaborative undertaking involving investigators from multiple disciplines and institutions in studying the shared governance of risk by the federal and state governments. The character of the response to extreme events is a direct consequence of priorities for addressing various risks, the capabilities of the participating organizations to incorporate discordant information, and the decisions made at multiple levels of government. This research systematically addresses federal influences on state risk priorities, state risk priorities, federal and state organizational response repertoires, and the organizational dynamics of response to discordant information. Research activities include case studies of selected federal and state organizations, empirical study of federal risk policy and programs, empirical study of risk attention in the 50 states, and systems-dynamic simulation of organizational capabilities and responses to extreme events.
The research links the systemic-level issues of policy direction and design with the micro-level issues of organizational capabilities and response. A new understanding of organizational choice will be developed that integrates the policy process attention-driven model used to study policy agenda-setting with systems modeling of organizational capabilities and responses for extreme events. The findings will help guide development of more flexible and more responsive intergovernmental approaches to risk management. This includes the design of federal programs, incentives for inducing state activities, and improvement of organizational responses to extreme events. The project engages graduate students and introduces undergraduate students to risk policy and politics.

This is a small grant for exploratory research to gather data on how the global communication network functioned around Hurricane Katrina, in terms of its use by various social groups. This timely research will provide insights into how emergency warning messages can be propagated through the social network. It will start by building an understanding of the nature of the communication network in New Orleans and the Gulf Coast, including connections with global communication networks, and the nature of the social group structure that overlay this communication network. The basic research questions to be addressed are: building models of how information flows in a communication network and taking into account the "trustability" of the information.

The enormity of the tragedy following Hurricane Katrina indicates a failure in an apparently otherwise well functioning global communication network, wired and wireless. Despite the fact that two to three days before Hurricane Katrina hit, the level of danger was known and broadcast, a large fraction of the population and the local administration did not trust the forecasts enough to take action. Technology by itself cannot ensure that the data are processed into information and delivered in a timely fashion in a form that is meaningful to the user and of value in emergency response decision-making. A significant component of how information flows through the society is intertwined with the social network dynamics of the society.

Individuals will not act upon information unless they consider the information trustworthy. This fact takes on special significance during a time of technological transition, as traditional mass media like newspapers and network television are supplemented or supplanted by online news and other computer-enabled communication media. The theoretical approach of this research postulates that there must be multiple trustworthy paths from the source of the information to the individual before some action is taken. This idea is used to build new measures of the quality of a social communication network relating to how well it will perform in conveying emergency warning messages. In turn, these measures can provide specific recommendations regarding how the network could be improved.

Modern means of communication, such as web-logs, chatrooms, and e-mail messaging, provide unprecedented opportunities for a vast number of people to express their opinions and communicate with other people, most of whom are not personal acquaintances.

On August 26, 2005, TheWall Street Journal published an article by Daniel Henninger, "A Quite Majority Replaces Vietnam's 'Silent Majority'." He writes: ". . . Richard Nixon . . . gave a famous speech in 1969. . . . The idea, of course, was that the daily attention commanded by the anti-war movement was missing a class of Americans who sat home seething at the behavior of protesters. Today, because of the Internet, no one has to seethe in silence, as wired activists in both parties proved in 2004's high-tech elections, and now. But it may be that the current infatuation with anti-Bush, anti-Iraq sentiment is again missing a political current flowing beneath the surface of the news, just as the media missed . . . the value voters in the 2004 election."

The political and social reality of our time includes a huge communication space, "the electronic society," which allows an ever growing number of people to express themselves and actively participate in the social life of the general society. It is expected that drastically increased ways of self-expression and communication should intensify the processes of forming and evolving social trends. The electronic space is so large that it demands sophisticated computer algorithms in order to address important questions and do meaningful analysis.

In any social network, links are formed and broken in a never ending dynamics that represents the evolution of the social network. As the network evolves, social groups form and evolve, and occasionally a social group may grow to a size large enough to represent a new movement or coalition. The goal of this research is to track and discover such coalitions as they form and evolve in the Blogosphere.

While technically it is easy to track the evolution of one particular actor of an electronic society, it is much more important and much more difficult to discover groups composed of actors that are holding "reasonably" close although not identical opinions, and to differentiate them from those with substantially different opinions. In addition to the immense amount of data to be processed, the researcher must be aware of the volatility of such groups, whose members may agree on some issues, and disagree on others.

The straightforward attempt to discover and characterize these groups might involve listing out topics and positions of the actors. This approach is practically impossible not only because of the time necessary to read (by humans) the publications, but also because of the difficulty in characterization: many nuances and subtleties may look contradictory and inconsistent. Using an automated system for reading would not be practical either as it would also require a substantial linguistic analysis of each article.

This research project, funded by the Ethics and Values Studies component of the Science and Society Program, examines the role of values in computational modeling, how these values are shaped by professional and organizational cultures, and the effects of values on the success of computational models as products. Computational models are used every day in a wide variety of products and policies. Such models are often treated as pure mathematical abstractions with no values content or ethical implications. However, these models are not pure abstractions, but rather they are only as good as their inputs, including the values of computational modelers. The research builds on a field study of a corporate research laboratory funded by NSF. The first major finding of the exploratory study was that the design and use of computational models is affected by both embedded and contextual values. The second major finding was that organizational culture plays a key role in influencing the computational modeling process. The third major finding was that values help to shape the success of models as products. Further research at additional field sites with different organizational cultures is necessary to determine the general validity of the findings and to examine the relationship between organizational culture and the values of computational modeling. The first field study was successful in demonstrating the validity and effectiveness of the method, and generated new research questions that require additional research. Based on the research objectives and the findings of the first field study, three hypotheses guide the research: 1) embedded and contextual values play important roles in all of the stages of the modeling process; 2) values embedded in and contextual to the design and use of computational models are tied to organizational and professional cultures; and 3) values embedded in and contextual to the design and use of computational models influence the success not only of the computational modeling process but also of computational models as products. The two remaining field sites for this research include an academic laboratory and a government laboratory. The research method, including interviews, surveys, participant observation, and focus groups, has been validated and refined through the first field study. Data collection and analysis will include three field site visits over a one-year period for each site. This project will lead to important products, including conference presentations, manuscripts for peer-reviewed journals, and a book manuscript. This study demonstrates the importance of values in computational modeling. In particular, the finding that both embedded and contextual values play an important role in the design and use of computational models is a novel and important finding for the literatures on the ethics of modeling, the ethics of computing, and value-sensitive design that merits further investigation. The study also demonstrates the influence of organizational and professional cultures on values in computational modeling. This research generates a better understanding of how values impact the success of the modeling process and of models as products. The findings of this study will improve practice by computer scientists by demonstrating the importance of ethical choices related to values in computational modeling. The findings will inform managers of computational modelers about the important role that values play in the success of computational models. This study also demonstrates the importance of professional and organizational codes of ethics. Managers need to be responsible in making and enforcing ethical standards within organizations, while modelers should be encouraged to follow both professional and organizational codes of ethics. In addition, the research contributes to ethics education for computational modelers and their managers. The findings of this study can be used for general classes in computing and information ethics as well as specific courses and training in professional ethics for computational modelers.

Modern global society is increasingly reliant on computing and information professionals to serve key roles in creating, managing, and maintaining the global computing and information infrastructure that is critical to research, education, commerce, and quality of life. As such, computing and information professionals need to learn not only technical skills but also how to resolve ethical issues such as in/outsourcing, intellectual property, and information privacy. Working in the new global economy requires that computing and information professionals are able to consider the range of cultural values and ethical perspectives as represented by leading thinkers such as Aristotle, Bentham, Buddha, Confucius, Gilligan, and Kant. To broaden and deepen the ethical perspectives of computing and information professionals, it is essential to develop and teach courses in computing and information ethics as part of professional graduate programs in computer science and the interdisciplinary information field. Further, to enable current and future computing and information professionals to appreciate and understand the relevance of ethics in their work, it is necessary to find educationally motivating ways to engage graduate students in professional computing and information programs to consider key ethical issues. In this project the PIs hope to accomplish this goal through development and evaluation of an educational simulation for computing and information ethics, which serves as the cornerstone for an innovative course focusing on the role of values and ethics in computing and information within a global society. Building on their prior research, the PIs will explore three main research questions: How do graduate students in a computing and information ethics course use educational simulation software to gain understandings of and hands-on experiences with important computing and information ethics issues such as intellectual property in a global society? Does geographical co-location have an impact on use of the simulation in the context of an internationally-oriented computing and information ethics graduate course with a diverse range of students? Do students in a graduate-level computing and information ethics course benefit most from interaction with peers, or with the software agents developed through this project?

Broader Impacts: Project outcomes will include a free and open-source simulation for computing and information ethics, which allows students both to participate in and learn from cases, and to develop and implement their own cases that they can then share with peers. The PIs will develop a novel and highly participatory course built around the simulation, which will be implemented in professional computing and information master's programs across the country and the world, and which will better prepare computing and information professionals to deal with ethical issues throughout their careers.

The project is investigating the diffusion of emergency relevant actionable information, such as warnings, through social media. Specifically, the research will assess warning models from social sciences in the context of social media, determine the contribution of social media to warnings of extreme events, and develop an algorithmic approach for processing voluminous amount of social media data in order to extract relevant and actionable information. The research combines on site interviews of emergency management personnel with processing and analyzing social media data. The algorithmic approach incorporates various data processing techniques with classic social network analysis methods. Additionally, a content analysis is used to evaluate the information hidden in social media data. The specific event that serves as an organizing focus of the research is a magnitude 9.0 earthquake and the resulting tsunami in Sendai, Japan.

The results of this research will enrich our understanding of the role of social media in the communication of warnings during extreme events. Additionally, this effort will provide suggestions on ways to incorporate social media in emergency management. Emergency managers will have a faster and more effective means to reach the public with emergency information. Moreover, this research offers an opportunity for new members of the research community, such as graduate student researchers from Rensselaer Polytechnic Institute and first generation undergraduate research assistants from Le Moyne College, to participate in a project whose results will offer recommendations for improving emergency management, and most importantly, provide insights for practice that can save lives.

The objective of this Rapid Research Grant (RAPID) award is to investigate the concept of restoration interdependencies amongst infrastructure systems in responding to extreme events. A restoration interdependency is defined as the need for an infrastructure manager to consider the restoration efforts of another infrastructure in decision-making about his or her infrastructure's restoration. For example, debris may need to be cleared from an area prior to rebuilding or replacing power lines in that area. This would imply a precedence interdependency between the debris removal and the power infrastructure: an event needs to occur in the debris removal prior to an event (the rebuilding) starting in the power infrastructure's restoration efforts. This research seeks to identify, classify, and determine the frequency of restoration interdependencies after Hurricane Sandy by (1) interviewing infrastructure managers involved in the restoration efforts and (2) analyzing electronic media.

The results of this research will contribute to the resiliency of a community by enhancing our knowledge of what an infrastructure manager must consider in determining an infrastructure's restoration efforts. This analysis will help infrastructure managers better understand the level of coordination or information-sharing required across restoration efforts in order to take into account these restoration interdependencies. It will further help determine how restoration efforts should be planned to robustly handle restoration interdependencies, thereby shortening the time required for the restoration of vital services after an extreme event.

The Arctic has been experiencing significantly longer ice-free, navigable maritime seasons, thereby changing the types of activities taking place in Arctic waters. Cruise ships are travelling through the Northwest Passage, oil exploration is occurring off the North Slope of Alaska, and the Northern Sea Route is seeing an increasing volume of cargo ships travelling through it. In Arctic Alaska, these tourism and industrial activities will occur far away from the infrastructure and resources of urban and industrial centers, limiting response capabilities when an emergency occurs in Arctic waters. For all of these reasons, there is a critical need to improve Emergency Response in the Arctic (ERA) to meet the increase in the demand for these capabilities. The scientific contribution of this research is to create prescriptive decision-making models that help to determine where, when, and how to make infrastructure investments to improve global ERA capabilities while also providing benefits to Arctic communities. Because the infrastructure required to improve ERA will be built and maintained in local Arctic communities, this project will involve Arctic stakeholders, including representatives from indigenous communities, to guide the research and help disseminate its results. This project contributes to the NSF's Big Idea on Navigating the New Arctic by: (1) safeguarding human and environmental welfare in increasing ERA capabilities and (2) working closely with local and indigenous populations to co-produce knowledge about the types of benefits potentially provided to communities should ERA infrastructure be located in them. Potential benefits include local management of ERA infrastructure and deployment of resources, training and workforce development opportunities, and improved transportation infrastructure.

This research will create new Operations Research (OR) models that not only account for where and when to make infrastructure investments to improve ERA capabilities but how to properly integrate these investments into the communities where they are located. To accomplish this, this project is creating an innovative methodology where social science research done in conjunction with local Arctic communities is conducted in a way that informs the creation of the OR models and, in later stages of the work, validates their results. Therefore, this research integrates methods across OR and social science that link economic, social, cultural, and technical feasibility and desirability by incorporating expert local knowledge into the planning process. The results of this research will transform our understanding of how to design ERA systems that have positive impacts in the local communities where the supporting infrastructure is built and maintained.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Microscopic imaging of tissue samples is a fundamental tool used for the diagnosis of various diseases and forms the workhorse of pathology and biological sciences. The clinically-established gold standard image of a tissue section is the result of a laborious process. This work will demonstrate the ability to virtually stain label-free tissue sections and will revolutionize the current paradigm for histological analysis.


To demonstrate deep learning-based virtual histology staining of label-free human tissue samples this proposal will use salivary gland, thyroid, kidney, liver and lung samples, and will use three commonly used stains: H&E (salivary gland and thyroid), Jones stain (kidney) and Masson's Trichrome (liver and lung). This proposal will determine the staining efficacy of the proposed approach for whole slide images and will blindly evaluate the virtually stained outputs with gold standard stained samples. The output of this proposed system will be validated by a group of pathologists who will compare histopathological features with the virtual staining technique against conventional histology techniques.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.